What GPU do I need to run antony66/whisper-large-v3-russian?

1.5B parameters, published in BF16. View on Hugging Face

1.5B
Parameters
BF16
Native precision
WhisperForConditionalGeneration
Architecture
automatic-speech-recognition
Pipeline

whisper-large-v3-russian is published by antony66 on Hugging Face, with 13,293 downloads and 103 likes to date. It's a WhisperForConditionalGeneration model built for automatic-speech-recognition, published natively in BF16.

VRAM required & cheapest live GPU fit

Required VRAM = weight size at each precision, plus a fixed overhead for activations and allocator fragmentation. Speech models don't build the same growing KV-cache a text model does. Memory scales primarily with input audio length. Full formula and assumptions: methodology.

Precision
Weight size
Required VRAM
Cheapest live fit
GPUs needed
Est. $/hr (full fit)
BF16
2.9 GB
3.4 GB
RTX 3070 (simplepod)
1
$0.050/hr
FP8 (quantized)
1.4 GB
1.7 GB
RTX 4070 (simplepod)
1
$0.080/hr
INT4 (quantized)
0.7 GB
0.9 GB
RTX 3070 (simplepod)
1
$0.050/hr

A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.

INT4 caveat: requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run whisper-large-v3-russian at its published (BF16) precision: 1× RTX 3070 on simplepod, at $0.050/hr per GPU ($0.050/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.

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